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The increasing intensity and frequency of high-temperature events in response to climate change can potentially impact the aviation industry, since aircraft takeoff and landing performances depend on near-surface air temperature. Previous studies have combined climate data with aircraft technical data to estimate the future impact of rising high temperatures on aircraft takeoff. They found a decrease of maximum takeoff weights and the lengthening of takeoff distances. The Mediterranean region is a climate change "hot spot" area, specially concerned by extreme high-temperatures increase. In this study, the magnitude and trends of the daily maximum near-surface temperature extremes in summer were analysed over major airports in Southwestern Europe. Trends in the period 1961–2014 were analysed from observations and reanalysis. Future changes by 2021–2050 and 2071–2100, with respect to 1961–2005, were analysed from simulations performed with Regional and Global Climate Models (RCMs and GCMs). Before assessing future climate projections, climate models were evaluated in present climate, and the RCM and GCM ensembles were compared to each other. No clear added value was found for RCMs over GCMs in present climate at the airport scale in these terms. GCMs project larger temperature changes than RCMs over the same locations. Multi-model ensemble mean projected changes under the RCP8.5 scenario range between + 1.7 and + 3.2 ∘ C by the near term, and between + 4.9 and + 8.5 ∘ C by the long term, across the airports and the RCM and GCM ensembles. This increase of high-temperature extremes would impact airport operations. Adaptation or mitigation policies would become necessary. [ABSTRACT FROM AUTHOR]

Transitional climate zone (TCZ) over East Asia is located between humid and arid regions, which is a highly sensitive and disaster-prone region especially under global climate change. Due to limited water resources, the atmospheric moisture availability has a dominant control on the precipitation variability. Hence, this study is motivated to reveal the key teleconnection patterns and associated moisture processes that govern the interannual variability of the summer precipitation over TCZ. In order to better diagnose moisture budget, the Lagrangian particle dispersion model FLEXPART is employed for quantifying contribution from moisture sources. Above all, the observational analysis highlights two critical modes, one is Eurasian teleconnection (EU) and the other is Circumglobal Teleconnection (CGT). As regards EU pattern, positive EU phase corresponds to ample precipitation in TCZ. In the presence of positive phase, it underlines a "+-+-" pattern of geopotential height anomalies stretching from western Europe to Mongolia plateau. In the context, the cyclonic flow and low pressure over Mongolia plateau act to enhance moisture flux from the west and the south and to prompt upward motions. Further moisture diagnoses illuminate largest increase of moisture uptake in monsoon dominated region, followed by the westerlies dominated region. However, the eventual contribution of summer monsoon is a little bit less than that of westerlies, due to the grand loss en route. In addition, the local evaporation exerts little impact. CGT propagates along the mid-latitude westerly jet, which is positively coupled with the precipitation in TCZ. Under the positive phase, there is an ascending motion over TCZ, which bears great resemblance to the EU case. However, unlike the result of moisture attribution in EU case, the southerly monsoon has the largest contribution followed by local effect, while the westerlies have little impact due to the cancellation of wetting and drying regimes along the pathway. [ABSTRACT FROM AUTHOR]

Ozone is the third most important greenhouse gas in driving global warming, mainly due to increased tropospheric ozone. About 50% of the growth of global tropospheric ozone since preindustrial time occurred during 1955–2005, with continued growth since then. This study quantifies the relative contributions of ozone changes during 1955–2005 to total observed global and Arctic climate changes by comparing CESM1 historical simulations with all anthropogenic and natural radiative forcings including realistic ozone changes, and with the same forcings except with constant ozone or well-mixed greenhouse gases (WMGHG). Results indicate that ozone changes during 1955–2005 have strongly enhanced the downwelling longwave flux and increased net shortwave flux at the surface, and thus significantly contributed about 0.15 °C of global mean surface warming, roughly 21%, 26% and 16% of the observed, all-forcing and WMGHG-driven trends, respectively. In the Arctic in the same period, corresponding ozone-driven warming was about 0.63 °C, roughly 48%, 40% and 25% of the same three trends. During 1979–2005, these ozone changes have markedly added about 0.25 × 106 km2 to the decrease in the Arctic sea ice extent (SIE), or roughly 25%, 48%, and 40% of the same three trends. Considering that the ozone-driven radiative forcing of about 0.22 (0.06) W·m−2 in 1955–2005 (1979–2005) was about 12% (6%) of the corresponding WMGHG forcing, ozone changes had contributed disproportionately to global and Arctic warming and Arctic sea ice decline during the second half of the twentieth century. Tropospheric ozone has shown relatively steady growth since 2006 and might have significantly contributed recent observed warming over the global and the Arctic. [ABSTRACT FROM AUTHOR]

The interaction of stratospheric chemistry with a changing climate from an abrupt CO2 quadrupling is assessed using the coupled atmosphere–ocean Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM). Two abrupt 4 × CO2 experiments were performed, one with interactive stratospheric chemistry and the other with a prescribed stratospheric chemistry that does not simulate stratospheric ozone response to 4 × CO2. The interactive and prescribed chemistry experiments simulate similar global mean surface temperature change. Nevertheless, interactive chemistry is critical to capture the Southern Hemisphere tropospheric midlatitude jet response to 4 × CO2. When stratospheric ozone response to 4 × CO2 is neglected, GEOSCCM overestimates Southern Hemisphere tropospheric circulation change. This stratospheric chemistry-induced climate impact has large seasonal variability. During the austral spring season September–October–November (SON), prescribed chemistry yields a stronger poleward shift and intensification of the Southern Hemisphere midlatitude tropospheric jet, surface wind stress, and the Southern Ocean meridional overturning circulation than occurs with interactive chemistry. In other seasons interactive and prescribed chemistry have similar effects on the Southern Hemisphere circulation. The seasonality of stratospheric chemistry-induced climate impact is related to the seasonality of Antarctic lower stratospheric ozone response to 4 × CO2. In contrast to this stratospheric ozone response to 4 × CO2, stratospheric ozone recovery from decline of the ozone depleting substances has its largest impact on the Southern Hemisphere tropospheric circulation in austral summer (December–January–February), but no effects in SON. It is found that the different seasonality for these two stratospheric ozone layer change scenarios is related to the different seasonality of tropopause meridional temperature gradient response. [ABSTRACT FROM AUTHOR]

Correct simulation of land surface energy balance is critically important in reliably projecting future climate change. In this study, simulated surface energy fluxes including net radiation, latent heat, and sensible heat from 22 CMIP6 models are evaluated against ERA5 reanalysis data during 1950–2014 over global land surface to assess the performance of CMIP6 models in simulating surface energy balance. Results reveal significant differences in seasonal and regional characteristics of CMIP6 model simulations in the surface energy flux predictions. Net radiation is slightly overestimated in JJA (June, July, August) but underestimated in DJF (December, January, and February). Most models overestimate net radiation in both seasons over Africa, Australia, and Latin America. The inter-model variability of biases is substantial in DJF net radiation simulations over Asia, Europe and Siberia, and North America, although there is a good agreement between simulations of selected models and the ERA5 reanalysis data in JJA except for Greenland. Moreover, models overestimate latent heat and underestimate sensible heat in DJF, although latent heat and sensible heat simulations match well with the reference values in JJA. Latent heat is overestimated in DJF over Australia, Europe and Siberia, and Latin America. Sensible heat is underestimated during DJF over Europe and Siberia and Latin America. The performance of CMIP6 in Rn simulation is better than LH simulation and SH simulation for both JJA and DJF. Findings from this study will provide useful references for surface energy data users and future model development. [ABSTRACT FROM AUTHOR]

In the coming few decades, projected increases in global temperature and humidity are generally expected to exacerbate human exposure to climate extremes (e.g., humid-heat and rainfall extremes). Despite the growing risk of humid-heat stress (measured by wet-bulb temperature), it has received less attention in East Africa, where arid and semi-arid climatic conditions prevail. Moreover, no consensus has yet been reached across models regarding future changes in rainfall over this region. Here, we screen Global Climate Models (GCMs) from CMIP5 and CMIP6 and use, for boundary conditions, simulations from only those GCMs that simulate successfully recent climatic trends. Based on these GCMs and Regional Climate Model (RCM) simulations, we project that annual mean temperature is likely to rise by 2 ℃ toward midcentury (2021–2050) ​at a faster rate than the global average (about 1.5 ℃), under the RCP8.5 and SSP5-8.5 scenarios, associated with more frequent and severe climate extremes. In particular, low-lying regions in East Africa will be vulnerable to severe heat stress, with an extreme wet-bulb temperature approaching or exceeding the US National Weather Service's extreme danger threshold of 31 ℃. On the other hand, population centers in the highlands of Ethiopia will receive significantly more precipitation during the autumn season and will see more extreme rainfall events, with implications for flooding and agriculture. The robustness of these results across all GCM and RCM simulations, and for both of CMIP5 and CMIP6 frameworks (CMIP: Coupled Model Inter-comparison Project) supports the reliability of these future projections. Our simulations of near-term climate change impacts are designed to inform the development of sound adaptation strategies for the region. [ABSTRACT FROM AUTHOR]

The present study investigated future temperature and precipitation changes over Greece using the Weather Research and Forecasting (WRF) model. WRF was driven by EC-EARTH over Greece at very high resolution for the historical period (1980–2004), along with projected simulations, in the near future (2025–2049) and far future (2075–2099) under the Representative Concentration Pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). Climatic variables were produced at 5-km grid spacing and 6-h interval. The historical simulation was evaluated against the available station observations. The analysis showed that the model underestimated the maximum temperatures and slightly overestimated the minimum temperatures. Also, the model simulated a small dry bias in precipitation with an excellent representation of the spatial patterns. The model projections for temperature under the two emission scenarios compared to the historical simulation revealed a robust magnitude of future warming with the most pronounced changes predominantly over the eastern areas of the country under the RCP8.5 in the far future. Projected precipitation changes were more evident in the far future with an overall decrease of the annual precipitation all over the eastern part of the country (with islands included) with the most dramatic reductions (above 40%) of seasonal precipitation observed under RCP8.5. Increases in the number of hot days were found everywhere with more pronounced changes over the plain areas under RCP8.5 in the far future. Significant increases of dry days were projected over the eastern part of the mainland and more intensely under RCP8.5 in the far future. [ABSTRACT FROM AUTHOR]

Understanding the cloud feedback (CFB) process remains a critical challenge for climate projection. While previous studies have mainly focused on the globe, the tropics, or the Southern Ocean, this study analyzes the long-term CFB over East Asia (EA) using data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and radiative kernels newly developed. We find that the overall CFBs over EA act to amplify warming in an annual scale, with mean values of 0.66 ± 0.47 and 0.63 ± 0.39 W m−2 K−1 for the SSP2-4.5 and SSP5-8.5 scenarios, respectively, although remarkable seasonal discrepancies. There are two distinct subregions: the positive center over the East Asian monsoon region, primarily due to the significant reduction in low cloud cover; the negative center over the Tibet Plateau, largely owing to the reduced high cloud cover and the ice-to-liquid conversion of cloud phase. Furthermore, the CFB over EA changes from negative to positive in the early 1980s, and then enhance at a rate faster than the global average until the early years of the twenty-first century, which may be linked with the weakening and subsequent recovery of the East Asian summer monsoon. Generally, inter-kernel uncertainty is markedly smaller than inter-model uncertainty; however, in regional scale, inter-kernel uncertainty is larger and inter-model uncertainty is smaller than those in the global scale. This feature implies that ignoring inter-kernel uncertainty may bring additional errors to regional CFB quantification. Notably, these results are comparable between the SSP2-4.5 and SSP5-8.5 scenarios, suggesting that CFB processes may be insensitive to emission scenarios. [ABSTRACT FROM AUTHOR]

The North Atlantic eddy-driven jet (EDJ) is an essential component of the Euro-Atlantic atmospheric circulation. It has been typically described in terms of latitude and intensity but this is not enough to fully characterize its variability and complex EDJ configurations. Here, we present a set of daily parameters of the EDJ based on low-tropospheric zonal wind data for the 1948–2020 period. They describe the intensity, sharpness, location, edges, tilt and other zonal asymmetries of the EDJ, therefore dissecting its structure beyond the latitudinal regimes. This allows for assessments of specific EDJ aspects and a multi-parametric treatment of EDJ configurations in a manageable way. Overall, variations in EDJ parameters reflect distinctive patterns of eddy forcing and wave breaking, with anticyclonic eddies playing a major role in shaping the EDJ structure. A multimodal behavior of the EDJ is only detected in latitude, which largely influences the longitudinal position of the EDJ. Other aspects of the EDJ are less constrained by the latitude and display a variety of configurations. Four multi-parametric states (northern, central, tilted and split EDJs) provide a satisfactory description of recurrent patterns of the EDJ. They participate in meridional migrations of the EDJ, but yield less dramatic transitions than viewed from the latitudinal perspective. Finally, the EDJ parameters help to better understand the EDJ influence on European climate. In many regions, latitude and intensity contain limited information on near-surface anomalies, and their signals can be masked by the additional effect of other EDJ parameters. [ABSTRACT FROM AUTHOR]

Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex's map by selecting those with the lowest Euclidean distance from Alex. We term these "analogues" of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. [ABSTRACT FROM AUTHOR]

Colombia is highly vulnerable to climate change which may be intensified due to the climatic effects of regional deforestation. Here, we quantify the impact of historical (1900–2011) land cover changes (LCC) and of global warming during ENSO events (CC) on precipitation, temperature and surface energy balance components by running the Weather Research and Forecasting model WRF v3.9 at 10 km resolution. We find that historical anthropogenic CC causes a mean temperature increase of 0.77 ± 0.02 °C in Colombia, which is more pronounced in high altitudes. Precipitation is enhanced by 0.98 ± 0.30 mm/day (+ 9%), particularly over forested areas and reduced at the Pacific coast. LCC imply a reduction of precipitation particularly above the Andes (− 0.48 ± 0.10 mm/day) and Caribbean Coast (− 0.67 ± 0.12 mm/day), where LCC effects dampen CC effects by 24% and 72%, respectively. La Niña tends to intensify LCC and CC effects in the Andes but dampens them at the Coast, roughly by a factor of two compared to El Niño impacts in both regions. At the subregional level, LCC and CC can have impacts of similar magnitude on precipitation highlighting the need to precisely account for both drivers in hydroclimatic assessments. Contrary to almost all observations and similar simulations with climate models, WRF simulates a cooling bias after historical deforestation in Colombia, even with alternative WRF land surface models. We identify two main sources of biases in the default WRF parametrization to explain this inaccuracy: (1) surface shortwave radiation reflected after deforestation is overestimated; (2) associated evapotranspiration loss is underestimated. Improved model representation and validation of tropical vegetation properties are necessary to provide more robust and confident projections. [ABSTRACT FROM AUTHOR]

A hybrid statistical dynamical downscaling method intended to emulate regional climate models is described and applied to Western Europe. The method is based on a constructed analogues algorithm, already used for statistical downscaling. For emulation, the statistical downscaling relationship is not derived from observations but from climate projections at low and high resolution. The hybrid approach therefore does not rely on the stationarity assumption inherent to conventional statistical downscaling. Within a perfect model framework, and using a large number of regional projections, the hybrid method is shown to reproduce climate change signals very well and to outperform a conventional statistical downscaling method also based on constructed analogues. The hybrid approach remains skillful even when applied to very low resolution climate data. In practice, two emulation modes exist. In the GCM/RCM mode, the downscaling relationship is built between a RCM and its forcing GCM. In the RCM/RCM mode, the relationship is built between a RCM and the same RCM after aggregation of its results to a low resolution grid. The large-scale climate change signal of the downscaled GCM is generally retained with the RCM/RCM mode, but not with the GCM /RCM mode. Additionally, the choice of the GCM/RCM pair used for learning leads to large differences in downscaling results at large scale (i.e. at low resolution) with the GCM /RCM mode, but not with the RCM/RCM mode. These results are explained by the differences that generally exist at large scale between projected changes by current RCMs and their forcing GCMs. Whether these differences are a testimony of a real added value of RCMs at large scale in the climate change context, or whether they have other causes, is therefore a crucial question. [ABSTRACT FROM AUTHOR]

Turbulent momentum and heat (sensible heat and latent heat) fluxes at the air-sea interface are key components of the whole energetic of the Earth's climate. The evaluation of these fluxes in the climate models is still difficult because of the large uncertainties associated with the reference products. In this paper we present an objective metric accounting for reference uncertainties to evaluate the annual cycle of the low latitude turbulent fluxes of a suite of IPSL climate models. This metric consists in a Hotelling T test between the simulated and observed field in a reduce space characterized by the dominant modes of variability that are common to both the model and the reference, taking into account the observational uncertainty. The test is thus more severe when uncertainties are small as it is the case for sea surface temperature (SST). The results of the test show that for almost all variables and all model versions the model-reference differences are not zero. It is not possible to distinguish between model versions for sensible heat and meridional wind stress, certainly due to the large observational uncertainties. All model versions share similar biases for the different variables. There is no improvement between the reference versions of the IPSL model used for CMIP3 and CMIP5. The test also reveals that the higher horizontal resolution fails to improve the representation of the turbulent surface fluxes compared to the other versions. The representation of the fluxes is further degraded in a version with improved atmospheric physics with an amplification of some of the biases in the Indian Ocean and in the intertropical convergence zone. The ranking of the model versions for the turbulent fluxes is not correlated with the ranking found for SST. This highlights that despite the fact that SST gradients are important for the large-scale atmospheric circulation patterns, other factors such as wind speed, and air-sea temperature contrast play an important role in the representation of turbulent fluxes. [ABSTRACT FROM AUTHOR]

Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales. [ABSTRACT FROM AUTHOR]

Climate models are vital to the assessment of the impacts of climate change in the Central African regions. Establishing how well models reproduce key processes is important to the confidence we attach to these tools. This study examines model representation of the September to November characteristics, such as location and intensity, of the African Easterly Jet (AEJ) north and south in a sample of 16 commonly evaluated CMIP5 and CMIP6 models and in two reanalyses (ERA5 and MERRA2). The analysis evolves to assess key drivers of the AEJ from energetic interactions, the characteristics of mid-level highs and thermal lows and the nature of surface thermal heating. Over West Africa, several models miss the southeast-northwest orientation of the AEJ-N core, leading to a gap of around 60 in the location of the jet while most CMIP5 models also fail to locate AEJ-S over southern Central Africa. In general, the spread of simulated AEJ locations around reanalyses is larger for the CMIP5 sample compared to CMIP6 equivalent models, indicating improvement from CMIP5 to CMIP6 in this 16 model subset. However, this improvement in some CMIP6 models (e.g. GISS-E2-1-G and MIROC6) is not related to a maximum surface meridional gradient in temperature. Most CMIP5 and CMIP6 models underestimate the surface temperature gradient over AEJ-N region. As a first order diagnostic of the jet's acceleration, most coupled models better simulate the atmospheric energetic interactions over AEJ-N region that leads to its strong contribution to AEJ-N maintenance compared to AEJ-S. This study strengthens our understanding of the mid-level circulation over Central Africa by detecting gaps in the mechanisms maintaining the AEJ in coupled models and highlights processes that should be improved in future ensembles. [ABSTRACT FROM AUTHOR]

Recent assessments of climate sensitivity per doubling of atmospheric CO2 concentration have combined likelihoods derived from multiple lines of evidence. These assessments were very influential in the Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) assessment of equilibrium climate sensitivity, the likely range lower limit of which was raised to 2.5 °C (from 1.5 °C previously). This study evaluates the methodology of and results from a particularly influential assessment of climate sensitivity that combined multiple lines of evidence, Sherwood et al. (Rev Geophys 58(4):e2019RG000678, 2020). That assessment used a subjective Bayesian statistical method, with an investigator-selected prior distribution. This study estimates climate sensitivity using an Objective Bayesian method with computed, mathematical priors, since subjective Bayesian methods may produce uncertainty ranges that poorly match confidence intervals. Identical model equations and, initially, identical input values to those in Sherwood et al. are used. This study corrects Sherwood et al.'s likelihood estimation, producing estimates from three methods that agree closely with each other, but differ from those that they derived. Finally, the selection of input values is revisited, where appropriate adopting values based on more recent evidence or that otherwise appear better justified. The resulting estimates of long-term climate sensitivity are much lower and better constrained (median 2.16 °C, 17–83% range 1.75–2.7 °C, 5–95% range 1.55–3.2 °C) than in Sherwood et al. and in AR6 (central value 3 °C, very likely range 2.0–5.0 °C). This sensitivity to the assumptions employed implies that climate sensitivity remains difficult to ascertain, and that values between 1.5 °C and 2 °C are quite plausible. [ABSTRACT FROM AUTHOR]

Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts. Therefore, this study first evaluates the capabilities of one 11-single run multi-model ensemble (CMIP6) and one 40-member single model initial-condition large ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature–precipitation correlations and their historical changes. Next, the ensembles' correlations for the end of the 21st century are compared. Over the historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalysis displays significant correlation changes, none of the ensembles can reproduce them, with internal variability representing only 30% on the inter-model variability. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes. In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation. These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations. [ABSTRACT FROM AUTHOR]

The present study uses observation-based gridded air temperature and precipitation datasets to investigate the spatiotemporal changes in meteorological drought from 1981 to 2020 in South Asia (SA). The drought characteristics i.e., duration, area, frequency, intensity, and severity are calculated using Run theory and the Standardized Precipitation Evapotranspiration Index (SPEI) on annual and seasonal timescales. SA is divided into four homogeneous subregions using the k-means clustering algorithm, while the trends were estimated using Sen's Slope estimator and modified Mann-Kendall (MMK) test. A state-of-the-art Bayesian Dynamic Linear (BDL) model was employed to assess the sub-regional drought variability and their possible links with large-scale atmospheric drivers such as the Indian Ocean Dipole (IOD), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO). It is found that the SA winter season experienced a significant drying long-term trend, especially southwestern and northeastern parts of SA. Drought durations show dipolar patterns with longer drought duration in the southwestern compared to the northern parts of SA. Notably, arid and semi-arid regions have shown significant drying trends in terms of their area, frequency, and severity, implying that meteorological droughts are relatively more severe in those regions. Similarly, the relationship varies over time between drought variability and climate drivers. In particular, the IOD has an impact on drought episodes over southwest SA relative to the northern parts and is mostly affected by the Sea surface temperature (SST) variability. The study results contribute to a better understanding of the meteorological drought characteristics over SA, which is important for disaster risk managers and policymakers to mitigate drought impacts. [ABSTRACT FROM AUTHOR]

The interactions between the tropical Indian Ocean and Pacific Ocean via the Walker circulation and the Indonesian Throughflow (ITF) play an important role in the inter-basin exchange and climate variations. The effects of the eastern Indian Ocean subsurface temperature conditions during the 2019 Indian Ocean dipole (IOD) event on the development of the 2020/2021 La Niña event are investigated of the National Marine Environmental Forecasting Center of China. Results of pacemaker experiments comparing the effects of the atmospheric bridge and the oceanic channel suggest that the subsurface temperature anomalies in the tropical Indian Ocean dominates the inter-basin forcing leading to the outburst of the 2020/2021 La Niña event. The strong subsurface cooling is found to propagate to the eastern equatorial Pacific Ocean through the Indonesian seas and induce a strong La Niña event at the end of 2020, showing the long memory of the oceanic channel dynamics and the amplification by the ocean-atmospheric coupling. In comparison, experiments forced by surface temperature anomalies over the tropical Indian Ocean show that the atmospheric bridge alone is unable to induce the onset of the 2020 La Niña. The results suggest the importance of the Indo-Pacific oceanic channel dynamics in ENSO forecasts. [ABSTRACT FROM AUTHOR]

The climate change projections of the Intergovernmental Panel on Climate Change are based on scenarios for future emissions, but these are not statistically-based and do not have a full probabilistic interpretation. Raftery et al. (Nat Clim Change 7:637–641, 2017) and Liu and Raftery (Commun Earth Environ 2:1–10, 2021) developed probabilistic forecasts for global average temperature change to 2100, but these do not give forecasts for specific parts of the globe. Here we develop a method for probabilistic long-term spatial forecasts of local average annual temperature change, combining the probabilistic global method with a pattern scaling approach. This yields a probability distribution for temperature in any year and any part of the globe in the future. Out-of-sample predictive validation experiments show the method to be well calibrated. Consistent with previous studies, we find that for long-term temperature changes, high latitudes warm more than low latitudes, continents more than oceans, and the Northern Hemisphere more than the Southern Hemisphere, except for the North Atlantic. There is a 5% chance that the temperature change for the Arctic would reach 16 ∘ C. With probability 95%, the temperature of North Africa, West Asia and most of Europe will increase by at least 2 ∘ C. We find that natural variability is a large part of the uncertainty in early years, but this declines so that by 2100 most of the overall uncertainty comes from model uncertainty and uncertainty about future emissions. [ABSTRACT FROM AUTHOR]

The impact of the enhancing Pacific-North American teleconnection (PNA) on the intensity of the first mode of SST anomalies (SSTa) in wintertime North Pacific [known as the Pacific decadal oscillation (PDO)-like SST pattern] under global warming is studied using reanalysis datasets and 12 selected CMIP5 models. The robust observational result of the PNA one month ahead of the PDO shows that the PNA has a great effect on the PDO-like SSTa. The intensities of PNA and PDO are defined with elimination of the ENSO signals to evaluate the direct impact of PNA on the PDO in the North Pacific under global warming. By comparing RCP8.5 and historical scenario of selected multi-models (PNA enhanced models), future projection illustrates that the PDO intensity will intensify 2.2 times its internal variability. Approximately 67% of the increase in PDO variations is contributed by the PNA-induced SSTa in the future warming scenario of multi-models ensemble mean. Models with stronger intensification of PNA variability tends to have larger magnitude of SSTa response in the North Pacific, which has more contributions to the enhancement of PDO intensity change in a warmer climate. This may shed some light on the projection of PDO variability and the relative role of PNA forcing under the global warming. [ABSTRACT FROM AUTHOR]

Three consecutive dry summers in western Europe (2018–2019–2020) had widespread negative impacts on society and ecosystems, and started societal debate on (changing) drought vulnerability and adaptation measures. We investigate the occurrence of multi-year droughts in the Rhine basin, with a focus on event probability in the present and in future warmer climates. Additionally, we investigate the temporally compounding physical drivers of multi-year drought events. A combination of multiple reanalysis datasets and multi-model large ensemble climate model simulations was used to provide a robust analysis of the statistics and physical processes of these rare events. We identify two types of multi-year drought events (consecutive meteorological summer droughts and long-duration hydrological droughts), and show that these occur on average about twice in a 30 year period in the present climate, though natural variability is large (zero to five events can occur in a single 30 year period). Projected decreases in summer precipitation and increases in atmospheric evaporative demand, lead to a doubling of event probability at 1 ∘ C additional global warming relative to present-day and an increase in the average length of events. Consecutive meteorological summer droughts are forced by two, seemingly independent, summers of lower than normal precipitation and higher than normal evaporative demand. The soil moisture response to this temporally compound meteorological forcing has a clear multi-year imprint, resulting in a relatively larger reduction of soil moisture content in the second year of drought, and potentially more severe drought impacts. Long-duration hydrological droughts start with a severe summer drought followed by lingering meteorologically dry conditions. This limits and slows down the hydrological recovery of soil moisture content, leading to long-lasting drought conditions. This initial exploration provides avenues for further investigation of multi-year drought hazard and vulnerability in the region, which is advised given the projected trends and vulnerability of society and ecosystems. [ABSTRACT FROM AUTHOR]

The atmospheric downward longwave radiation at the Earth's surface (Ld) is an important parameter for investigating greenhouse effects and global climate changes. Reanalysis data have been widely applied to obtain surface radiation components. Since new generation reanalysis data have been released, a comprehensive evaluation of the Ld predictions from the latest reanalysis data using ground measurements is still necessary. In this study, the Ld estimates of four representative reanalysis data (CFSR, JRA-55, ERA5, and MERRA2) were evaluated using ground observations at 383 stations from the AmeriFlux, AsiaFlux, BSRN, Buoy, FLUXNET, and SURFEAD networks. The evaluation results manifested that the overall root mean square errors (mean bias errors) of daily mean Ld values over the global surface were 21.1 (− 1.8) W m−2, 22.4 (− 3.9) W m−2, 19.3 (− 3.6) W m−2, 25.2 (− 12.6) W m−2, and 20.5 (3.1) W m−2 for CFSR, JRA-55, ERA5, MERAA2, and CERES-SYN, respectively. Compared with the CERES-SYN satellite retrievals, the ERA5 (CFSR) daily mean Ld estimates had relatively smaller overall root mean square errors (mean bias errors) over the global land surface. Over the global ocean surface, the JRA-55 daily mean Ld estimates had comparable mean bias errors (MBEs) with CERES-SYN. After removing the MBEs, the best annual mean Ld estimate was 344.0 (± 3) W m−2 over the global surface of 2001 to 2020. The spatial distributions and long-term trends of Ld for the selected four reanalysis data and CERES-SYN were also investigated in this study. The comprehensive assessment of the Ld products from reanalysis data and satellite retrievals in this study would be helpful for climate change studies. [ABSTRACT FROM AUTHOR]

Results from a multiregression analysis of the global and sea surface temperature anomalies for the period 1950-2011 are presented where among the independent variables multidecade oscillation signals over various oceanic areas are included. These indices are defined in analogy with the Atlantic Multidecadal Oscillation (AMO) index. Unexpectedly we find that a strong multidecade oscillation signal echoing the AMO is also present in the Western and Northwestern Pacific region. The results indicate that naturally induced climate variations seem to be dominated by two internal variability modes of the ocean-atmosphere system: AMO and El Niño Southern Oscillation, with a marked geographical dichotomy in their respective areas of dominance. As the AMO index is directly derived from SST data the finding that the AMO signal is present on a large fraction of the global oceanic surface casts doubt on its use as an independent explanatory variable in regression analyses of the global surface temperature anomalies. [ABSTRACT FROM AUTHOR]

Recent numerical studies in stratospheric dynamics and its variability as well as climate, have highlighted the need of more observational analyses to improve simulation of the West African monsoon (WAM). In this paper, activity and spectral characteristics of short-scale vertical waves (wavelengths <4 km) are analysed in equatorial coastal and tropical lower stratosphere during the WAM. A first detailed description of such waves over West Africa is derived from high-resolution vertical profiles of temperature and horizontal wind obtained during Intensive Observation Period of the African Monsoon Multidisciplinary Analyses (AMMA) Campaign 2006. Monthly variation of wave energy density is revealed to trace the progression of the inter-tropical convergence zone (ITCZ) over West Africa. Mesoscale inertia gravity-waves structures with vertical and horizontal wavelengths of 1.5-2.5 and 400-1100 km respectively and intrinsic frequencies of 1.1-2.2 f or periods <2 days are observed in the tropical LS with intense activity during July and August when the WAM is installed over the tropical West Africa. Over equatorial region, gravity waves with intrinsic frequencies of 1.4-4 f or periods <5.2 days, vertical wavelength of 2.1 km and long horizontal wavelengths of 1300 km are intense during the WAM coastal phase. From July to October, gravity waves with intrinsic frequencies of 1.2-3.8 f or periods <6 days, vertical wavelength of 2.1 km and horizontal wavelengths of 1650 km are less intense during the WAM Sahelian phase of the WAM, March-June. Unlike potential energy density, kinetic energy density is observed to be a good proxy for the activity of short-scale vertical waves during the WAM because quasi-inertial waves are dominant. Long-term wave activity variation from January 2001 to December 2009, highlights strong year-to-year variation superimposed on convective activity and quasi-biennial oscillation-like variations especially above tropical stations. [ABSTRACT FROM AUTHOR]

Transitional Climate Zone (TCZ) over East Asia, characterized by semi-arid climate, is ecologically fragile environment with limited water resources, making atmospheric moisture supply being the key influential factor. This study investigates the moisture sources of summer (JJA) rainfall in the TCZ over East Asia and associated impact during 1979–2010 with the Lagrangian particle dispersion model. Seven moisture source regions and associated contribution are quantified: Eurasia continent to northwest of the TCZ (EC, 32.14%), central-eastern China (CEC, 16.62%), western Pacific Ocean (WPO, 8.58%), South China Sea and Indonesia (SCSI, 2.99%), Bay of Bengal (BOB, 1.4%), Arabian Sea (AS, 0.71%) and local evaporation (TCZ, 32.58%). The direct moisture contribution from ocean (13.67%) is much less than those from the continent (81.34%), due to the great loss en-route. In particular, the local evaporation not only contributes the most moisture among 7 selected source regions, but also exerts the greatest influence in summer precipitation variability in TCZ. Furthermore, the moisture related to summer rainfall over TCZ conveyed by westerlies and monsoon are discriminated according to the dominant system of moisture source regions. It is found that moisture contributions from summer monsoon system (30.3%) and the mid-latitude westerlies (32.14%) dominant areas are quite close. However, further analysis shows that summer monsoon system takes more responsibility for inter-annual fluctuation of summer precipitation in TCZ from the perspective of moisture supply, followed by local evaporation and mid-latitude westerlies. [ABSTRACT FROM AUTHOR]

The global mean surface temperature is rising and under climate change it is expected to increase in the future. The changes are not uniform across the world and the impact assessment at a regional level is, thus, a necessity. Bangladesh, a tropical low-lying monsoon region, is greatly at risk under climate change. However, no attempt has been carried out to assess the changes in frequency of extreme temperatures (return period values) under the backdrop of climate change which is required in practical applications. The aim of this study is to investigate the changes in temperature extremes: maximum (Tx) and minimum (Tn) at the daily time scale under climate change in Bangladesh. The multi-model ensemble methodology comprised of five general circulation models and two emission scenarios from CMIP6 framework was used to evaluate the impact in two future time horizons: 2021–2060 and 2061–2100. The L-moment based frequency analysis with annual maxima (minima) data was used to quantify extreme temperatures in terms of return levels. With this approach, the identification of a probability distribution is one important aspect which is investigated in this study. We have found that the generalized normal (GNO) distribution is quite appropriate of describing the temperature extremes. There is a significant increase in location parameter which signifies a uniform shift for the extreme tail of the distribution. There are no appreciable overall changes in scale and shape parameter. The temperature extremes (both Tx and Tn) are expected to increase noticeably compared to the present observed condition. There is a tendency to have a greater estimate of extremes in the far future than the near future. The greater estimate is also perceived under the high emission scenario in comparison to the medium emission scenario. The country average change in 20-year return period value of Tx by the end of this century is about 3–4.7 °C compared to the corresponding changes of 2.4 to 3.7 °C for Tn. The findings are expected to assist in the evaluation of climate change impacts and adaptation strategies in Bangladesh. [ABSTRACT FROM AUTHOR]

Here we use observations and simulations from 40 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), under preindustrial, historical, and a high emission scenario (RCP8.5) to provide estimates of Victorian cool season (April–October) rainfall for the coming century. This includes a new method which exploits recent research that estimated the relative contribution of external forcing and natural variability to the observed multidecadal decline in cool season rainfall in Victoria from 1997. The new method is aimed at removing the influence of external forcing on Victoria's cool-season rainfall, effectively rendering a stationary time-series. The resulting historical record is then modified by scaling derived from the mean projected change evident in climate models out to 2100. The results suggest that the median value of the All-Victoria rainfall PDF will decrease monotonically over the remainder of the twenty-first century under RCP8.5. The likelihood that All-Victoria rainfall in any given year from 2025 onward will be below the observed 5th percentile of the observations (291 mm) increases monotonically, becoming three times larger by the end of the century. The new method is assessed using cross-validation and its ability to hindcast observed multidecadal rainfall change. The latter indicates that CMIP5 models poorly replicate recent interdecadal rainfall change. So, while we have more confidence in the new method because it accounts for the non-stationarity in the observed climate, limitations in the CMIP5 models results in us having low confidence in the reliability of the estimated future rainfall distributions. [ABSTRACT FROM AUTHOR]

A high-resolution third-generation wave model based on unstructured grids, WAVEWATCH III (WW3), was used to study the projected future wave climate of Bass Strait and south-east Australia under two different greenhouse gas emission scenarios (SSP1-2.6 and SSP5-8.5). The wave model, forced with winds from the Australian ACCESS-CM2 Global Climate Model, shows good agreement with coastal long-term buoy observations and an independent WW3 hindcast dataset over the historical period 1985–2014. The projected mean significant wave height ( H s ) for SSP5-8.5 by the end of the twenty-first century (2071–2100) shows a robust increase for the majority of the domain, but a decrease in nearshore regions, mainly due to projected decreases in local wind speed. The increase in H s for SSP1-2.6 is relatively small. Seasonal variations show that H s (SSP5-8.5) is primarily influenced by Southern Ocean swell in spring and winter and local winds prevail in summer and autumn. Hs percentiles show a stronger increase in extreme wave climate for SSP5-8.5 than for SSP1-2.6. Extreme value H s for SSP1-2.6 shows a projected decrease in western regions of the domain and an increase in the east. Extreme value H s for SSP5-8.5 shows a decrease in the nearshore areas of Victoria. This study shows that projected wave climate changes in south-east Australia may have potential implications for Tasmanian and Victorian coastline stability. [ABSTRACT FROM AUTHOR]

Climate models project that a reduction in the Antarctic sea-ice extent due to global warming in the future would exert an influential role on the climate system. However, due to the coupled nature of the climate system and various feedbacks present, the underlying mechanism is not well understood. The present study attempts to investigate the potential effects of the model projected Antarctic sea-ice loss on the climate system and understand the underlying mechanism causing such changes using coupled model simulations. The investigation suggests that the projected sea-ice loss will result in the localized surface warming accompanied with tropospheric warming that will be experienced globally. The surface evaporation will enhance, accompanied by an increase in the precipitation and cloud cover around Antarctica's coastal periphery, with marginal changes observed over the continent's interiors. The strength of the atmospheric circulation in the Southern Hemisphere will change significantly, resulting in an enhancement in the Polar cell and katabatic flow accompanied by a marginal reduction in the Ferrel and Hadley cells, causing an equatorial shift in the jet's position. The eddy transport will also significantly weaken, leading to an overall reduction in the poleward energy transport at higher latitudes. These atmospheric circulation changes are essentially driven by the radiative budget, with more absorbed short-wave radiation reducing the poleward transport requirements. Compared to the reported uncoupled simulations studies, the remote global influence of sea ice loss noted in these coupled simulations which extends up to the Arctic highlights the strong pole-to-pole connections in the climate system through atmospheric and oceanic circulations. [ABSTRACT FROM AUTHOR]

Total least squares (TLS) or multivariate orthogonal regression is widely used as a remedy for attenuation bias in climate signal detection or "optimal fingerprinting" regression. But under some circumstances it overcorrects and imparts an upward bias, as well as generating extremely unstable and imprecise coefficient estimates. While there has been increasing attention paid recently to the validity of TLS-based confidence intervals, there has been no corresponding examination of coefficient bias problems. This note explains why they are pertinent and presents a Monte Carlo simulation to illustrate the hazards of using TLS in a signal detection application without testing whether the modeling context makes it a suitable choice. TLS is not automatically preferred over OLS even when explanatory variables are believed to contain random errors. Notably it can be sufficiently biased to cause false positives when explanatory signals are negatively correlated, and the bias gets worse as the signal-noise ratio on the explanatory variables rises. Additionally TLS should not be used on its own for climate signal detection inferences since if the no-signal null is true, TLS is generally inconsistent whereas OLS attenuation bias disappears. [ABSTRACT FROM AUTHOR]

Disentangling the links between terrestrial vegetation changes and astronomical forcing as well as CO2 is of great help to understand the sensitivity of contemporary vegetation and predict future vegetation and climate changes, yet it remains challenging. Given the distinct differences in astronomical configurations and CO2 concentration between Marine Isotope Stage (MIS) 11 and 13, here we investigate the role of astronomical forcing and CO2 on global vegetation changes during these two interglacials based on transient simulations performed with the model LOVECLIM1.3. Our results show that during these two interglacials, astronomical forcing plays a dominant role on the vegetation evolution, with the effect of CO2 being relatively small. The effect of astronomical forcing on vegetation can be explained successively by the relationship between climate (temperature, precipitation) and the astronomical parameters and by the relationship between vegetation and climate. The relative effect of precession and obliquity on vegetation strongly depends on regions and on interglacials. In general, obliquity plays a more important role on vegetation variations during MIS-11, while precession is more important during MIS-13. Our results also reveal a clear half-precession cycle (~ 10 ka) in the variations of temperature, precipitation and vegetation in the tropical area during MIS-13, as a direct response to the tropical insolation. However, no obvious half-precession cycle is simulated during MIS-11 due to its weak precession variation but large obliquity variation, indicating that half-precession cycle is not stable in time. [ABSTRACT FROM AUTHOR]

A comprehensive assessment of twenty-first century climate change in the European Alps is presented. The analysis is based on the EURO-CORDEX regional climate model ensemble available at two grid spacings (12.5 and 50 km) and for three different greenhouse gas emission scenarios (RCPs 2.6, 4.5 and 8.5). The core simulation ensemble has been subject to a dedicated evaluation exercise carried out in the frame of the CH2018 Climate Scenarios for Switzerland. Results reveal that the entire Alpine region will face a warmer climate in the course of the twenty-first century for all emission scenarios considered. Strongest warming is projected for the summer season, for regions south of the main Alpine ridge and for the high-end RCP 8.5 scenario. Depending on the season, medium to high elevations might experience an amplified warming. Model uncertainty can be considerable, but the major warming patterns are consistent across the ensemble. For precipitation, a seasonal shift of precipitation amounts from summer to winter over most parts of the domain is projected. However, model uncertainty is high and individual simulations can show change signals of opposite sign. Daily precipitation intensity is projected to increase in all seasons and all sub-domains, while the wet-day frequency will decrease in the summer season. The projected temperature change in summer is negatively correlated with the precipitation change, i.e. simulations and/or regions with a strong seasonal mean warming typically show a stronger precipitation decrease. By contrast, a positive correlation between temperature change and precipitation change is found for winter. Among other indicators, snow cover will be strongly affected by the projected climatic changes and will be subject to a widespread decrease except for very high elevation settings. In general and for all indicators, the magnitude of the change signals increases with the assumed greenhouse gas forcing, i.e., is smallest for RCP 2.6 and largest for RCP 8.5 with RCP 4.5 being located in between. These results largely agree with previous works based on older generations of RCM ensembles but, due to the comparatively large ensemble size and the high spatial resolution, allow for a more decent assessment of inherent projection uncertainties and of spatial details of future Alpine climate change. [ABSTRACT FROM AUTHOR]

Early reanalyses are less than optimal for investigating the regional effects of ozone depletion on Southern Hemisphere (SH) high-latitude climate because the availability of satellite sounder data from 1979 significantly improved their accuracy in data sparse regions, leading to a coincident inhomogeneity. To determine whether current reanalyses are better at SH high-latitudes in the pre-satellite era, here we examine the capabilities of the European Centre for Medium-range Weather Forecasts (ECMWF) fifth generation reanalysis (ERA5), the Twentieth Century Reanalysis version 3 (20CRv3), and the Japanese Meteorological Agency (JMA) 55-year reanalysis (JRA-55) to reproduce and help explain the pronounced change in the relationship between the Southern Annular Mode (SAM) and Antarctic near-surface air temperatures (SAT) between 1950 and 1979 (EARLY period) and 1980–2020 (LATE period). We find that ERA5 best reproduces Antarctic SAT in the EARLY period and is also the most homogeneous reanalysis across the EARLY and LATE periods. ERA5 and 20CRv3 provide a good representation of SAM in both periods with JRA-55 only similarly skilful in the LATE period. Nevertheless, all three reanalyses show the marked change in Antarctic SAM-SAT relationships between the two periods. In particular, ERA5 and 20CRv3 demonstrate the observed switch in the sign of the SAM-SAT relationship in the Antarctic Peninsula: analysis of changes in SAM structure and associated meridional wind anomalies reveal that in these reanalyses positive SAM is linked to cold southerly winds during the EARLY period and warm northerly winds in the LATE period, thus providing a simple explanation for the regional SAM-SAT relationship reversal. [ABSTRACT FROM AUTHOR]

Understanding the spatial–temporal changes in glacier mass balance and associated drivers on the Tibetan Plateau (TP) is important for predicting future water supplies and glacier-related hazards. However, the comparative study of changes in glacier mass balance in different regions of the same glacierized massif on the TP remains scarce. Combining the reconstructed detailed mass balance time-series from 1970 to 2015 for Ningchan No.1 Glacier in the eastern Qilian Mountains and Qiyi Glacier in the western Qilian Mountains using the energy and mass balance model in this work with the published mass balance data from different glaciers, we find that interannual changes in glacier mass balance are broadly similar in different regions of the Qilian Mountains. These interannual changes are primarily driven by variations in ablation-season (June–September) air temperature (Ta), which impact albedo and melt by changing snowfall and incoming longwave radiation (Lin). We link such interannual mass balance variability to the combination of changes in atmospheric circulation over Europe and changes in sea surface temperature (SST) in the Northwest Pacific during the ablation season which can cause the changes in Ta across the Qilian Mountains. In addition, we find a trend of increasingly negative glacier mass balance across the Qilian Mountains from 1970–1994 compared to 1995–2015. This interdecadal trend is driven by higher ablation-season Ta through increasing Lin and through increasing precipitation falling as rain. Lastly, higher glacier mass loss in the east than in the west Qilian Mountains from 1970–1994 and 1995–2015 was mainly caused by lower glacier area-altitude distribution, as well as a reduction in ablation-season precipitation in the eastern Qilian Mountains. [ABSTRACT FROM AUTHOR]

The Arctic Coordinated Regional Downscaling Experiment (Arctic-CORDEX) uses regional climate models (RCMs) to downscale selected Fifth Coupled Model Intercomparison Project simulations, allowing trend validation and projection on subregional scales. For 1986–2015, the CORDEX seasonal-average near-surface temperature (tas), wind speed (sfcWind), precipitation (pr) and snowfall (prsn) trends are generally consistent with analyses/observations for the Arctic Ocean regions considered. The projected Representative Concentration Pathway 8.5 (RCP8.5) 2016–2100 subregional annual tas trends range from 0.03 to 0.18 K/year. Projected annual pr and prsn trends have a large inter-model spread centered around approximately 5.0 × 10–8 mm/s/year and −5.0 × 10–8 mm/s/year, respectively, while projected sfcWind summer and winter trends range between 0.0 and 0.4 m/s/year. For all variables except prsn, and sometimes total precipitation, the driving general circulation model (GCM) dominates the trends, however there is a tendency for the GCMs to underestimate the sfcWind trends compared to the RCMs. Subtracting the Arctic-Ocean mean from subregional trends reveals a consistent, qualitative anomaly pattern in several variables and seasons characterized by greater-than or average trends in the central and Siberian Arctic Ocean and lesser or average trends in the Atlantic Sector and the Bering Sea, related to summer sea-ice trends. In particular, a strong proportional relationship exists between the summer sea-ice concentration and fall tas and sfcWind trend anomalies. The RCP4.5 annual, multi-model mean trends are 35–55% of the corresponding RCP8.5 trends for most variables and subregions. [ABSTRACT FROM AUTHOR]

Regional projections of extreme precipitation intensity (EPI) are strongly influenced by changes of "extreme ascent", i.e. ascending air during periods of extreme precipitation. Earlier studies have suggested that long-term changes in eddy length scale and vertical stability are key factors influencing extreme ascent projections, but these mechanisms have yet to be confirmed with controlled model experiments. In this study, we perform such controlled experiments using a cloud-resolving model (CRM). The selected CRM domains are three locations over the subtropical Atlantic Ocean where global climate models consistently project weakening of extreme ascent with accordingly decreased EPI. At each study location, four to ten pairs of 20-year-maximum precipitation events are simulated with the CRM, with each pair consisting of an event during the historical period (1981–2000) and an event during the future period (2081–2100). Large-scale forcings for these events are derived from members of an initial condition ensemble of the Canadian Earth System Model version 2 (CanESM2). These experiments reveal that, in all three study locations, weakening of differential cyclonic vorticity advection (dCVA) is a key driver of projected decreases in extreme ascent and EPI. Possible mechanisms responsible for weakening dCVA are discussed. Although there is evidence that EPI in the CRM has different sensitivity to large-scale forcings than CanESM2, the role of dCVA changes may nonetheless be important to consider for EPI changes in the real world. [ABSTRACT FROM AUTHOR]

This study investigates the association of spring (April–May) Arctic sea ice melt with simultaneous surface air temperature (SAT) over mid-high latitudes of Eurasia from 1979 to 2019 by using observational datasets and simulation experiments. The results show that spring SAT anomalies associated with Arctic sea ice melt display a dipole pattern over Eurasia. A high Arctic sea ice melt corresponds to positive SAT anomalies over northern Eurasia and negative SAT anomalies over most of Asia. The 500 hPa geopotential height anomalies exhibit a wave train structure, and a dominant positive center is located over the Ural Mountains with two negative centers over East Asia and western Europe. This atmospheric circulation anomaly differs from the traditional Eurasian pattern and the North Atlantic-Eurasian teleconnection pattern due to their different spatial modes. Simulation experiments forced by Arctic sea ice anomalies reproduce the major characteristics of observational associations. Observations and numerical simulations indicate that high Arctic sea ice melt years are often associated with heavy sea ice in winter-spring, which is favorable for the occurrence of Arctic anticyclonic circulation anomaly and lead to a positive SAT anomaly in the Arctic. The Arctic warming not only strengthens polar zonal westerly winds by increasing local baroclinicity, but also weakens zonal winds in mid-latitude through a reduction meridional temperature gradient. It may contribute to the Arctic anticyclonic anomalies enhancement, and then induces a wave train southeastward propagating into the mid-low latitudes. This configuration of atmospheric circulation anomalies provides favorable conditions for the SAT variations over Eurasia. [ABSTRACT FROM AUTHOR]

The western North Pacific Subtropical High (WNPSH) is a key circulation system regulating the East Asian climate, and its area has crucial indicative for summer precipitation in China. In this study, we established the model for classification prediction of summer WNPSH area via the Gaussian Naive Bayes (GNB). By setting different category proportions and different training set sample sizes, we investigated the prediction ability of GNB and its dependent on the data sample size. After comparing the prediction performance of GNB with tree models which were commonly used in short-term climate prediction, it was found that the accuracy scores (ACC) and balanced accuracy scores (BCC) of GNB were statistically significantly higher than tree models. Additionally, under different category classification criteria, the ACC and BCC of GNB could maintain above 0.77 and 0.75, respectively. Especially for anomalous categories, the recalls values could maintain above 0.5. These results indicate that the GNB had very strong prediction ability for the summer WNPSH area and could also better predict the degree of anomalous WNPSH area. Moreover, under different training set sample sizes, the ACC of GNB could be maintained above 0.6, which suggests that the GNB was less dependent on the data sample size and could reduce the limitation of abrupt interdecadal changes in climate on the available data sample size to some extent. This study reveals strong prediction ability of GNB for the summer WNPSH area, which also has high reference value for the research of other short-term climate prediction problems. [ABSTRACT FROM AUTHOR]

Infrastructure and transportation systems on which northern communities rely are exposed to a variety of climatic hazards over a broad range of scales. Efforts to adapt these systems to the rapidly warming Arctic climate require high-quality climate projections. Here, a state-of-the-art regional climate model is used to perform simulations at 4-km resolution over the eastern and central Canadian Arctic. These include, for the first time over this region, high-resolution climate projections extending to the year 2040. Validation shows that the model adequately simulates base climate variables, as well as variables hazardous to northern engineering and transportation systems, such as degrading permafrost, extreme rainfall, and extreme wind gust. Added value is found over coarser resolution simulations. A novel approach integrating climate model output and machine learning is used for deriving fog—an important, but complex hazard. Hotspots of change to climatic hazards over the next two decades (2021–2040) are identified. These include increases to short-duration rainfall intensity extremes exceeding 50%, suggesting Super–Clausius–Clapeyron scaling. Increases to extreme wind gust pressure are projected to reach 25% over some regions, while widespread increases in active layer thickness and ground temperature are expected. Overall fog frequency is projected to increase by around 10% over most of the study region by 2040, due to increasing frequency of high humidity conditions. Given that these changes are projected to be already underway, urgent action is required to successfully adapt northern transportation and engineering systems located in regions where the magnitude of hazards is projected to increase. [ABSTRACT FROM AUTHOR]

A fuzzy classification scheme that results in physically interpretable meteorological patterns associated with rainfall generation is applied to classify homogeneous regions of boreal summer rainfall anomalies in Germany. Four leading homogeneous regions are classified, representing the western, southeastern, eastern, and northern/northwestern parts of Germany with some overlap in the central parts of Germany. Variations of the sea level pressure gradient across Europe, e.g., between the continental and maritime regions, is the major phenomenon that triggers the time development of the rainfall regions by modulating wind patterns and moisture advection. Two regional climate models (REMO and CCLM4) were used to investigate the capability of climate models to reproduce the observed summer rainfall regions. Both regional climate models (RCMs) were once driven by the ERA-Interim reanalysis and once by the MPI-ESM general circulation model (GCM). Overall, the RCMs exhibit good performance in terms of the regionalization of summer rainfall in Germany; though the goodness-of-match with the rainfall regions/patterns from observational data is low in some cases and the REMO model driven by MPI-ESM fails to reproduce the western homogeneous rainfall region. Under future climate change, virtually the same leading modes of summer rainfall occur, suggesting that the basic synoptic processes associated with the regional patterns remain the same over Germany. We have also assessed the added value of bias-correcting the MPI-ESM driven RCMs using a simple linear scaling approach. The bias correction does not significantly alter the identification of homogeneous rainfall regions and, hence, does not improve their goodness-of-match compared to the observed patterns, except for the one case where the original RCM output completely fails to reproduce the observed pattern. While the linear scaling method improves the basic statistics of precipitation, it does not improve the simulated meteorological patterns represented by the precipitation regimes. [ABSTRACT FROM AUTHOR]

Since the 1970s, scientists have developed statistical methods intended to formalize detection of changes in global climate and to attribute such changes to relevant causal factors, natural and anthropogenic. Detection and attribution (D&A) of climate change trends is commonly performed using a variant of Hasselmann's "optimal fingerprinting" method, which involves a linear regression of historical climate observations on corresponding output from numerical climate models. However, it has long been known in the field of time series analysis that regressions of "non-stationary" or "trending" variables are, in general, statistically inconsistent and often spurious. When non-stationarity is caused by "integrated" processes, as is likely the case for climate variables, consistency of least-squares estimators depends on "cointegration" of regressors. This study has shown, using an idealized linear-response-model framework, that if standard assumptions hold then the optimal fingerprinting estimator is consistent, and hence robust against spurious regression. In the case of global mean surface temperature (GMST), parameterizing abstract linear response models in terms of energy balance provides this result with physical interpretability. Hypothesis tests conducted using observations of historical GMST and simulation output from 13 CMIP6 general circulation models produced no evidence that standard assumptions required for consistency were violated. It is therefore concluded that, at least in the case of GMST, detection and attribution of climate change trends is very likely not spurious regression. Furthermore, detection of significant cointegration between observations and model output indicates that the least-squares estimator is "superconsistent", with better convergence properties than might previously have been assumed. Finally, a new method has been developed for quantifying D&A uncertainty, exploiting the notion of cointegration to eliminate the need for pre-industrial control simulations. [ABSTRACT FROM AUTHOR]

The Arctic sea ice loss during the past several decades plays an important role in driving global climate change. Herein we explore the effects of Arctic sea ice loss on global ocean circulations and ocean heat redistribution. We find that in response to Arctic sea ice loss, oceans are taking up heat from the atmosphere via sensible and latent heat fluxes mainly in the subpolar North Atlantic. Meanwhile, Arctic sea ice loss induced ocean circulation changes could redistribute the taken heat, which, however, is timescale-dependent. Within a decade after Arctic sea ice loss, the Atlantic meridional overturning circulation (AMOC) is little altered such that most of the taken heat is locally stored in the Atlantic. On a multidecadal to centennial timescale, the AMOC decelerates redistributing the heat to other basins through interbasin ocean heat exchanges. In the Indo-Pacific Ocean, an anomalous ocean circulation is generated manifesting an abnormal northward flow near the surface, which imports about one-third of the redistributed heat from the Atlantic, via the Southern Ocean and into the Indian Ocean. Meanwhile, the Indonesia Throughflow weakens giving rise to an anomalous ocean heat transport from the Indian to Pacific Ocean. As a result, both Indian and Pacific Oceans are warmed on a multidecadal to centennial timescale. The Arctic sea ice loss also induces a "mini" global warming with a pronounced lower to middle tropospheric warming in the Southern Hemisphere. Accordingly, the Southern Hemisphere westerly winds poleward intensify to modulate the Deacon Cell and residual MOC in the Southern Ocean. Along with the ocean circulation changes and associated variations in ocean heat transport across the boundary between the Southern Ocean and Atlantic/Indo-Pacific Oceans, two-thirds of the ocean heat imported from the Atlantic remains in the Southern Ocean. [ABSTRACT FROM AUTHOR]

Mechanistic causes for sea level (SL) change patterns are analyzed as they emerge from the Coupled Model Intercomparison Project Phase 6 (CMIP6) endorsed Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) coupled climate experiments imposing individual forcing anomalies in wind stress, heatflux and freshwater flux to the Max-Planck-Institute Earth System Model (MPI-ESM). It appears that the heat flux perturbations have the largest effect on the sea level. In contrast, the direct impact of momentum and freshwater flux anomalies on SL anomalies appear to be limited to some region e.g. the Southern Ocean, Arctic Ocean and to some extent the North Pacific and North Atlantic Ocean. We find that thermosteric changes dominate the total SL change over large parts of the global ocean, except north of 60 °N where halosteric changes prevail. An analysis of added and redistributed components of heat and freshwater further suggests that the added component dominates the thermosteric SL and the redistributed component dominates the halosteric SL. Due to feedback processes a superposition of all forcing components together leads to the simulated sea level changes in each individual experiment. As a result, large surface heat flux anomalies over the Atlantic lead to wind stress change outside of the Atlantic through teleconnections, which in turn appear to be the primary driving agent for changes of sea level outside of the Atlantic in all three experiments. The associated wind driven Sverdrup stream function implicates that outside of the Atlantic most of the feedback can be explained by changes in the Sverdrup circulation. [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs), periods of anomalously warm sea surface temperature (SST) which can have significant impacts on marine ecosystems, have increased in frequency and severity over recent decades. Many coastal systems (e.g., coral reefs) are particularly vulnerable to warm-season heat stress when temperature can exceed organisms' thermal thresholds and lead to mass mortality. While many studies have examined the change of the warm-season heat stress occurrence over time, e.g., for coral reefs, there has been less analysis of the thermal properties of heat stress events. Here we examine the trend in the characteristics of warm-season heat stress (referred to as warm-season MHWs) at the global-scale from 1985 to 2019, using multiple metrics for each of duration, peak intensity, accumulated heat stress and heating rates. The results show that warm-season MHWs have become more frequent, longer-lasting, featured higher peak intensity and accumulated heat stress across most of the ocean over the past 4 decades. Furthermore, decomposition of the trends in warm-season MHW properties shows that the increased accumulated heat stress was predominantly driven by the increased duration rather than the increased intensity. The results contribute to improving the understanding of warm-season MHWs, which may help inform the prediction of their impacts on marine ecosystems as well as marine conservation and management under climate change. [ABSTRACT FROM AUTHOR]

The earth system model (ESM) mostly provides an output of hydrological variables at a daily scale, such as precipitation. Finer temporal scale data of precipitation is required for assessing the impact of climate change on floods, especially in small-size urban and mountainous watersheds which are vulnerable to floods. This study enhanced population-based nonparametric temporal downscaling (PNTD) to downscale daily precipitation to 10-min precipitation (P10M), and tested it in the Jinju area, South Korea, that includes both urban and mountainous areas. Results indicated that the enhanced PNTD model reproduced the key statistics of the P10M data and the statistical characteristics of extreme events represented by the annual maximum precipitation (AMP) series of different durations. Also, the daily precipitation of 19 ESMs with the base and future scenarios, called shared socio-economic pathways, for 245 and 585 conditions were applied and downscaled to P10M data. It was found that the future P10M precipitation scenarios were downscaled satisfactorily by preserving the difference between base and future scenarios of the AMP data. Also, results showed that the uncertainty from ESMs was about 10 times larger than from temporal downscaling and it indicated that the uncertainty in temporal downscaling can be acceptable. The P10M data can be employed for deriving intensity–duration–frequency curves needed for designing urban drainage systems and other hydraulic and hydrologic structures and for installing flood warning systems. [ABSTRACT FROM AUTHOR]

This work offers a new perspective on the predictions of the wind fields of typhoons in Hong Kong, which takes into consideration the effects of climate change. An integrated model combining (1) the Monte-Carlo simulation methodology, (2) four future climate change scenarios gathered from the shared socioeconomic pathways (SSPs), and (3) a refined typhoon wind field model combined with the probabilistic models of typhoon key parameters has been developed and validated herein, by employing the four climate scenarios reported in Phase 6 of the Coupled Model Intercomparison Project. The direct consequence is that the probability distributions of the six key parameters of a typhoon's wind fields—translational velocity, approach angle, central pressure deficit, the radius of maximum wind, the distance of closest approach, and annual occurrence rate—should be modified according to the increase in sea surface temperatures. In this study, the key parameters are drawn from the modified distributions and input into the refined wind field models to predict the typhoon wind field in the future with preset climate change scenarios. Via the Monte-Carlo simulations of 10,000 virtual typhoons, the probabilistic characteristics of the typhoon wind speeds and directions are predicted. More specifically, the predictions at the Waglan Island in Hong Kong are compared with the corresponding statistics calculated from the current meteorology database, and the comparisons suggest that the rise of SST will result in slight increases in typhoon wind speeds. In addition, the typhoon wind direction, in general, drifts counterclockwise due to the increase in SSTs. [ABSTRACT FROM AUTHOR]

Precipitation changes over the Tibetan Plateau (TP), "Asian Water Tower", greatly affect water resources of the surrounding countries. A dipole pattern in summer precipitation trend over the TP is observed for 1961–2013, increasing over the north TP (NTP) and decreasing over the south TP (STP). Since the TP is one of the most vulnerable regions to climate change in the world, it is of great importance to investigate the role of anthropogenic forcing in the TP precipitation changes. Moisture budget analysis based on reanalysis reveals that the precipitation trends over NTP and STP are dominated by thermodynamic and dynamic terms of vertical moisture advection, respectively. Southward shift in the summer subtropical Asian westerly jet (AWJ) over the west of TP and northward shift in AWJ over the east of TP collaboratively result in the increase and decrease in dynamic component over NTP and STP, respectively. Here, we successfully detect the anthropogenic contribution to the NTP summer precipitation trends using the attribution experiments from the CLIVAR Climate of the 20th Century Plus Project (C20C+). The drying trends over STP are mainly controlled by internal variability, and the anthropogenic forcing is favorable for the drying trends. The impacts of anthropogenic forcing are twofold. First, human activity induced warming increases the specific humidity over TP, increasing the thermodynamic component of moisture budget. Second, the warming trend caused by anthropogenic forcing is unevenly distributed over the Eurasian continent, leading to the southward (northward) shift of AWJ over the west (east) of TP, favoring more precipitation over the NTP but less precipitation over the STP. This study provides evidence of the importance of anthropogenic forcing on the water cycle changes over the TP. [ABSTRACT FROM AUTHOR]

Recent climate change in the Arctic has been rapid and dramatic, leading to numerous physical and societal consequences. Many studies have investigated these ongoing and projected future changes across a range of climatic variables, but surprisingly little attention has been paid to wind speed, despite its known importance for sea ice motion, ocean wave heights, and coastal erosion. Here we analyzed future trends in Arctic surface wind speed and its relationship with sea ice cover among CMIP5 global climate models. There is a strong anticorrelation between climatological sea ice concentration and wind speed in the early 21st-century reference climate, and the vast majority of models simulate widespread future strengthening of surface winds over the Arctic Ocean (annual multi-model mean trend of up to 0.8 m s−1 or 13%). Nearly all models produce an inverse relationship between projected changes in sea ice cover and wind speed, such that grid cells with virtually total ice loss almost always experience stronger winds. Consistent with the largest regional ice losses during autumn and winter, the greatest increases in future wind speeds are expected during these two seasons, with localized strengthening up to 23%. As in other studies, stronger surface winds cannot be attributed to tighter pressure gradients but rather to some combination of weakened atmospheric stability and reduced surface roughness as the surface warms and melts. The intermodel spread of wind speed changes, as expressed by the two most contrasting model results, appears to stem from differences in the treatment of surface roughness. [ABSTRACT FROM AUTHOR]